In the digital age, organizations must manage increasingly large volumes of data. Some organizations may store data within databases to structure and/or organize their data. In environments with large databases, common objects such as tables and indexes may have billions of rows and occupy several gigabytes of storage. To save on storage costs, organizations may wish to compress database data.
Unfortunately, existing techniques for compressing database data may impose limitations on which data may be compressed and/or may impose unacceptable costs when compressing data. For example, some traditional database systems may include compression features for compressing updates to databases but not for existing data within the databases. Some traditional database systems may allow the compression of an existing table, but at the cost of relocating the entire table to a new container. Furthermore, compressing certain portions of databases (such as indexes with unique columns) may yield little storage savings but impose significant performance costs. Accordingly, the instant disclosure identifies and addresses a need for additional and improved systems and methods for compressing databases.